A vehicle can be configured to operate in an autonomous mode in which the vehicle navigates through an environment with little or no input from a driver. Such an autonomous vehicle can include one or more sensors that are configured to detect information about the environment in which the vehicle operates. One such sensor is a light detection and ranging (LIDAR) device.
A LIDAR device can estimate distance to environmental features while scanning through a scene to assemble a “point cloud” indicative of reflective surfaces in the environment. Individual points in the point cloud can be determined by transmitting a laser pulse and detecting a returning pulse, if any, reflected from an object in the environment, and determining the distance to the object according to the time delay between the transmitted pulse and the reception of the reflected pulse.
A LIDAR device may thus include a laser, or set of lasers, and may rapidly and repeatedly scan across a scene to provide continuous real-time information on distances to reflective objects in the scene. Combining the measured distances and the orientation of the laser(s) while measuring each distance allows for associating a three-dimensional position with each returning pulse. In this way, a three-dimensional map of points indicative of locations of reflective features in the environment can be generated for the entire scanning zone.
One challenge in using LIDARs can be range aliasing. Range aliasing relates to the appearance of false echoes, such as when a system cannot disambiguate between a signal scattered from one particular range and a signal scattered from other ranges based on the generated data. For example, in the context of LIDARs, range aliasing can refer a return signal from outside a LIDAR's maximum unambiguous range being interpreted to be within the LIDAR's maximum unambiguous range.